{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Adaptive Grade for Difficulty\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/adaptive_grade_difficulty.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "540c855245ed4a7e863d7bce842beba3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "86868c6290784c80bfb6f150dd3efc9d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1, 1, 2, 3, 4]\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            state[:,0], self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        keys = torch.tensor([1, 2, 3, 4])\n",
    "        keys = keys.view(1, -1).expand(X[:, 1].long().size(0), -1)\n",
    "        index = (X[:, 1].long().unsqueeze(1) == keys).nonzero(as_tuple=True)\n",
    "        X_rating = X[:, 1].clone().float()\n",
    "        X_rating[index[0]] = self.w[13+index[1]]\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = torch.exp(np.log(0.9) * X[:,0] / state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X_rating - self.w[15])\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='none')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels).sum()\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels).sum()\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels).mean()\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels).mean()\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d34edd1606044e4aa7f78f85a49c9d1d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3341\n",
      "Loss in testset: 0.3123\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f126c795baac4ddf9e17eca1209ae65f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2588, 1.8518, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 1.0, 2.0, 3.0, 4.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2693a03bd9eb4c318705f89391c51eb6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3316\n",
      "Loss in testset: 0.3101\n",
      "iteration: 15360\n",
      "w: [1.2327, 2.0554, 5.1373, -1.1997, -1.088, 0.05, 1.4938, -0.15, 0.906, 2.071, -0.1484, 0.3521, 0.9206, 0.5501, 1.2787, 3.5518, 4.4925]\n",
      "iteration: 30720\n",
      "w: [1.2313, 2.0664, 5.0297, -1.729, -1.099, 0.05, 1.524, -0.15, 0.9286, 2.0724, -0.1729, 0.314, 0.9077, 0.7599, 1.0641, 3.5076, 4.9535]\n",
      "iteration: 46080\n",
      "w: [1.2312, 2.067, 4.8913, -1.7956, -1.1817, 0.05, 1.4989, -0.1671, 0.9122, 2.0735, -0.1869, 0.375, 0.8647, 0.8029, 0.8947, 3.5441, 5.2513]\n",
      "Loss in trainset: 0.3167\n",
      "Loss in testset: 0.2971\n",
      "iteration: 60984\n",
      "w: [1.2312, 2.067, 4.838, -1.9408, -1.2198, 0.05, 1.4677, -0.2182, 0.8769, 2.0059, -0.2629, 0.348, 0.8212, 0.7635, 0.832, 3.621, 5.1441]\n",
      "iteration: 76344\n",
      "w: [1.2312, 2.067, 4.6682, -1.9298, -1.184, 0.05, 1.5111, -0.1534, 0.9143, 2.029, -0.2429, 0.2767, 0.8222, 0.8695, 0.7999, 3.5753, 5.1704]\n",
      "iteration: 91704\n",
      "w: [1.2312, 2.067, 4.6982, -2.0061, -1.2695, 0.05, 1.4603, -0.2102, 0.8643, 2.0684, -0.207, 0.3076, 0.7486, 0.8629, 0.6818, 3.6256, 5.2859]\n",
      "Loss in trainset: 0.3163\n",
      "Loss in testset: 0.2967\n",
      "iteration: 106608\n",
      "w: [1.2312, 2.067, 4.6339, -1.9954, -1.261, 0.05, 1.4821, -0.1767, 0.8801, 2.0286, -0.2493, 0.3379, 0.6598, 0.8971, 0.6496, 3.6468, 5.1991]\n",
      "iteration: 121968\n",
      "w: [1.2312, 2.067, 4.6191, -2.001, -1.2578, 0.05, 1.4727, -0.1735, 0.8678, 2.0587, -0.2198, 0.3633, 0.6513, 0.8995, 0.6536, 3.6409, 5.209]\n",
      "iteration: 137328\n",
      "w: [1.2312, 2.067, 4.6135, -2.0146, -1.2651, 0.05, 1.47, -0.1648, 0.8629, 2.0525, -0.2266, 0.368, 0.6475, 0.9092, 0.6325, 3.6504, 5.2012]\n",
      "iteration: 152688\n",
      "w: [1.2312, 2.067, 4.6129, -2.013, -1.2651, 0.05, 1.464, -0.1711, 0.8567, 2.0474, -0.2317, 0.363, 0.6436, 0.9082, 0.6329, 3.6511, 5.1995]\n",
      "Loss in trainset: 0.3161\n",
      "Loss in testset: 0.2966\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3202\n",
      "Loss in testset: 0.3397\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e17053fd6b2e4b5abb9c153891dd2e26",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0143, 2.047, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 1.0, 2.0, 3.0, 4.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e44f1aeb6cde4741b5a09a85e41f924e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3172\n",
      "Loss in testset: 0.3381\n",
      "iteration: 15360\n",
      "w: [2.1098, 2.1547, 5.0387, -1.3137, -1.2648, 0.05, 1.5905, -0.15, 1.0055, 2.0739, -0.175, 0.2593, 1.1089, 0.4247, 1.0998, 3.7028, 4.5585]\n",
      "iteration: 30720\n",
      "w: [2.1147, 2.1603, 4.8244, -1.7251, -1.1217, 0.0788, 1.5213, -0.1915, 0.9738, 2.033, -0.2412, 0.3703, 1.0368, 0.693, 1.0961, 3.4875, 4.8826]\n",
      "iteration: 46080\n",
      "w: [2.1149, 2.1605, 4.6424, -1.9918, -0.9585, 0.05, 1.4444, -0.1964, 0.9167, 1.9787, -0.2986, 0.3317, 0.8994, 1.1454, 0.9931, 3.2781, 5.0807]\n",
      "Loss in trainset: 0.3030\n",
      "Loss in testset: 0.3240\n",
      "iteration: 60942\n",
      "w: [2.1149, 2.1605, 4.5727, -1.8622, -1.1177, 0.0675, 1.3476, -0.2174, 0.8196, 2.0284, -0.251, 0.3457, 0.9314, 1.2305, 0.6971, 3.3752, 5.1999]\n",
      "iteration: 76302\n",
      "w: [2.1149, 2.1605, 4.469, -1.8577, -1.0921, 0.05, 1.3344, -0.1857, 0.8115, 2.0151, -0.2639, 0.3655, 0.8319, 1.3381, 0.6246, 3.3657, 5.1418]\n",
      "iteration: 91662\n",
      "w: [2.1149, 2.1605, 4.3247, -1.7924, -0.9674, 0.05, 1.3619, -0.1505, 0.8355, 1.9955, -0.2823, 0.3407, 0.7614, 1.4639, 0.7007, 3.2498, 5.1295]\n",
      "Loss in trainset: 0.3024\n",
      "Loss in testset: 0.3235\n",
      "iteration: 106524\n",
      "w: [2.1149, 2.1605, 4.3669, -1.8309, -1.0962, 0.05, 1.3415, -0.1701, 0.8076, 2.0258, -0.2483, 0.3619, 0.7685, 1.3599, 0.59, 3.3757, 5.1161]\n",
      "iteration: 121884\n",
      "w: [2.1149, 2.1605, 4.3483, -1.8261, -1.1274, 0.05, 1.3535, -0.15, 0.8175, 2.0326, -0.2397, 0.3597, 0.744, 1.3288, 0.5649, 3.4116, 5.1]\n",
      "iteration: 137244\n",
      "w: [2.1149, 2.1605, 4.3502, -1.8323, -1.13, 0.05, 1.3427, -0.1541, 0.8047, 2.0369, -0.2344, 0.3644, 0.7426, 1.3422, 0.5446, 3.4141, 5.0905]\n",
      "iteration: 152604\n",
      "w: [2.1149, 2.1605, 4.3481, -1.8301, -1.1295, 0.05, 1.3412, -0.1558, 0.8028, 2.0349, -0.2361, 0.363, 0.7393, 1.342, 0.5455, 3.414, 5.0893]\n",
      "Loss in trainset: 0.3023\n",
      "Loss in testset: 0.3234\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3255\n",
      "Loss in testset: 0.3286\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d90ddf8273a4a89bc21c3222839b335",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2804, 1.8287, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 1.0, 2.0, 3.0, 4.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "499dcf6852cc44a4b8c1daf9a17dafc8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3233\n",
      "Loss in testset: 0.3258\n",
      "iteration: 15360\n",
      "w: [1.2103, 1.9125, 5.1692, -1.3413, -1.2188, 0.05, 1.5629, -0.1732, 0.9421, 2.0388, -0.1663, 0.3382, 1.0683, 0.4383, 1.189, 3.6444, 4.6714]\n",
      "iteration: 30720\n",
      "w: [1.2066, 1.9168, 5.0337, -1.646, -1.171, 0.05, 1.4842, -0.1743, 0.8864, 1.9555, -0.2675, 0.352, 0.7583, 0.5763, 1.181, 3.5213, 5.0168]\n",
      "iteration: 46080\n",
      "w: [1.2065, 1.917, 4.8913, -1.8725, -1.1483, 0.05, 1.4916, -0.1651, 0.8836, 1.9969, -0.2378, 0.3559, 0.5912, 0.6759, 1.0995, 3.5223, 4.9714]\n",
      "Loss in trainset: 0.3094\n",
      "Loss in testset: 0.3107\n",
      "iteration: 60966\n",
      "w: [1.2065, 1.917, 4.7513, -1.7334, -1.2282, 0.05, 1.4515, -0.1875, 0.8347, 2.0394, -0.2061, 0.375, 0.521, 0.6332, 1.0167, 3.5621, 5.1104]\n",
      "iteration: 76326\n",
      "w: [1.2065, 1.917, 4.6339, -1.7133, -1.2322, 0.05, 1.4325, -0.1894, 0.81, 2.0318, -0.2159, 0.3359, 0.5217, 0.7139, 0.924, 3.5665, 5.1354]\n",
      "iteration: 91686\n",
      "w: [1.2065, 1.917, 4.5524, -1.8369, -1.227, 0.05, 1.4866, -0.15, 0.8585, 2.056, -0.1882, 0.3436, 0.4868, 0.7351, 0.9083, 3.5679, 5.1223]\n",
      "Loss in trainset: 0.3091\n",
      "Loss in testset: 0.3104\n",
      "iteration: 106572\n",
      "w: [1.2065, 1.917, 4.5522, -1.9218, -1.2679, 0.0579, 1.4886, -0.1544, 0.8573, 2.0416, -0.2029, 0.3416, 0.4183, 0.686, 0.8911, 3.5966, 5.1561]\n",
      "iteration: 121932\n",
      "w: [1.2065, 1.917, 4.527, -1.9292, -1.2654, 0.05, 1.4766, -0.1731, 0.843, 2.0401, -0.2041, 0.3503, 0.3939, 0.6808, 0.8862, 3.6176, 5.1035]\n",
      "iteration: 137292\n",
      "w: [1.2065, 1.917, 4.5357, -1.9548, -1.2799, 0.05, 1.4662, -0.1766, 0.8314, 2.0465, -0.1972, 0.359, 0.3897, 0.6724, 0.8725, 3.6261, 5.1178]\n",
      "iteration: 152652\n",
      "w: [1.2065, 1.917, 4.5341, -1.9543, -1.2802, 0.05, 1.464, -0.178, 0.8289, 2.0443, -0.1995, 0.3587, 0.3883, 0.6726, 0.8708, 3.6281, 5.1141]\n",
      "Loss in trainset: 0.3090\n",
      "Loss in testset: 0.3103\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.5175, 2.0482, 4.4983, -1.9324, -1.2249, 0.05, 1.4231, -0.1683, 0.8294, 2.0421, -0.2225, 0.3615, 0.5903, 0.9743, 0.683, 3.5644, 5.1343]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,3d,6d,11d,20d,1.2m,2.0m,3.4m,5.6m,9.0m\n",
      "difficulty history: 0,8.4,8.2,8.0,7.8,7.6,7.5,7.3,7.2,7.1,6.9\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,20d,1.4m,2.7m,4.9m,8.8m,1.2y,2.1y,3.4y\n",
      "difficulty history: 0,6.4,6.3,6.2,6.2,6.1,6.0,5.9,5.8,5.8,5.7\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,16d,1.3m,2.9m,6.2m,12.1m,1.9y,3.3y,5.6y,9.3y\n",
      "difficulty history: 0,4.5,4.5,4.5,4.5,4.5,4.5,4.5,4.5,4.5,4.5\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,25d,2.3m,5.5m,1.0y,2.1y,4.0y,7.3y,12.8y,21.3y\n",
      "difficulty history: 0,2.6,2.7,2.8,2.8,2.9,3.0,3.1,3.1,3.2,3.3\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(round(float(np.log(requestRetention)/np.log(0.9) * states[0])), 1)\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6139, 4.4983])\n",
      "tensor([16.0770,  4.4983])\n",
      "tensor([39.4713,  4.4983])\n",
      "tensor([88.4991,  4.4983])\n",
      "tensor([185.0624,   4.4983])\n",
      "tensor([9.1302, 7.5123])\n",
      "tensor([ 2.8846, 10.0000])\n",
      "tensor([4.0326, 9.7249])\n",
      "tensor([5.7770, 9.4636])\n",
      "tensor([8.6363, 9.2153])\n",
      "tensor([13.1741,  8.9795])\n",
      "tensor([19.9606,  8.7554])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,16,39,88,185,9,3,4,6,9,13,20\n",
      "difficulty history: 0,4.5,4.5,4.5,4.5,4.5,7.5,10.0,9.7,9.5,9.2,9.0,8.8\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1,round(float(np.log(requestRetention)/np.log(0.9) * states[0])))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3265, loss after: 0.3092, improvement: 0.0173\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9279\n",
      "RMSE: 0.0191\n",
      "[0.09800162 0.89168805]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.2396\n",
      "RMSE: 0.0495\n",
      "[0.32253918 0.62019263]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: -0.4384\n",
      "RMSE: 0.0902\n",
      "[-0.5779679   1.53830089]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9230\n",
      "RMSE: 0.0216\n",
      "[0.05162601 0.95517245]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: -0.2084\n",
      "RMSE: 0.0392\n",
      "[0.46757214 0.52526355]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row3_col5, #T_5e260_row8_col1, #T_5e260_row12_col1 {\n",
       "  background-color: #bdbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row3_col7 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row4_col2, #T_5e260_row4_col3, #T_5e260_row11_col2 {\n",
       "  background-color: #e5e5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row4_col4, #T_5e260_row6_col2 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row4_col5, #T_5e260_row10_col6 {\n",
       "  background-color: #e1e1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row4_col7, #T_5e260_row8_col6, #T_5e260_row9_col6, #T_5e260_row10_col4 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col1 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col2, #T_5e260_row6_col1 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col3, #T_5e260_row10_col2 {\n",
       "  background-color: #fffdfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col4 {\n",
       "  background-color: #b5b5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col5, #T_5e260_row7_col5, #T_5e260_row8_col3, #T_5e260_row9_col2 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col6, #T_5e260_row9_col1 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row5_col7 {\n",
       "  background-color: #ffa5a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row6_col3, #T_5e260_row7_col4, #T_5e260_row7_col6 {\n",
       "  background-color: #ffd9d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row6_col4 {\n",
       "  background-color: #ffb5b5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row6_col5 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row6_col6, #T_5e260_row9_col4 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row6_col7 {\n",
       "  background-color: #ff6d6d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row7_col1 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row7_col2 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row7_col7 {\n",
       "  background-color: #ff0101;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row8_col2 {\n",
       "  background-color: #d1d1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row8_col4 {\n",
       "  background-color: #ffb1b1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row8_col5 {\n",
       "  background-color: #ff9595;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row8_col7 {\n",
       "  background-color: #ff0d0d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row9_col0, #T_5e260_row12_col4 {\n",
       "  background-color: #8d8dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row9_col3 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row9_col5 {\n",
       "  background-color: #ffd1d1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row9_col7 {\n",
       "  background-color: #ff6565;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row10_col1 {\n",
       "  background-color: #b1b1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row10_col5 {\n",
       "  background-color: #ffa1a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row10_col7, #T_5e260_row11_col7 {\n",
       "  background-color: #ff1515;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row11_col3 {\n",
       "  background-color: #ffe1e1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row11_col5 {\n",
       "  background-color: #ff8d8d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row11_col6, #T_5e260_row13_col1 {\n",
       "  background-color: #adadff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_5e260_row12_col2 {\n",
       "  background-color: #9595ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row13_col2 {\n",
       "  background-color: #8585ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_5e260_row14_col2 {\n",
       "  background-color: #6969ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_5e260\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_5e260_level0_col0\" class=\"col_heading level0 col0\" >1</th>\n",
       "      <th id=\"T_5e260_level0_col1\" class=\"col_heading level0 col1\" >3</th>\n",
       "      <th id=\"T_5e260_level0_col2\" class=\"col_heading level0 col2\" >4</th>\n",
       "      <th id=\"T_5e260_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
       "      <th id=\"T_5e260_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
       "      <th id=\"T_5e260_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
       "      <th id=\"T_5e260_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
       "      <th id=\"T_5e260_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row0\" class=\"row_heading level0 row0\" >1.400000</th>\n",
       "      <td id=\"T_5e260_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_5e260_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_5e260_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_5e260_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_5e260_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_5e260_row0_col5\" class=\"data row0 col5\" >2.59%</td>\n",
       "      <td id=\"T_5e260_row0_col6\" class=\"data row0 col6\" ></td>\n",
       "      <td id=\"T_5e260_row0_col7\" class=\"data row0 col7\" >2.76%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row1\" class=\"row_heading level0 row1\" >1.960000</th>\n",
       "      <td id=\"T_5e260_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_5e260_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_5e260_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_5e260_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_5e260_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_5e260_row1_col5\" class=\"data row1 col5\" >-3.72%</td>\n",
       "      <td id=\"T_5e260_row1_col6\" class=\"data row1 col6\" ></td>\n",
       "      <td id=\"T_5e260_row1_col7\" class=\"data row1 col7\" >-0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row2\" class=\"row_heading level0 row2\" >2.740000</th>\n",
       "      <td id=\"T_5e260_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_5e260_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_5e260_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_5e260_row2_col3\" class=\"data row2 col3\" >4.75%</td>\n",
       "      <td id=\"T_5e260_row2_col4\" class=\"data row2 col4\" ></td>\n",
       "      <td id=\"T_5e260_row2_col5\" class=\"data row2 col5\" >-0.23%</td>\n",
       "      <td id=\"T_5e260_row2_col6\" class=\"data row2 col6\" >-2.35%</td>\n",
       "      <td id=\"T_5e260_row2_col7\" class=\"data row2 col7\" >-0.09%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row3\" class=\"row_heading level0 row3\" >3.840000</th>\n",
       "      <td id=\"T_5e260_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_5e260_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_5e260_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_5e260_row3_col3\" class=\"data row3 col3\" >-1.56%</td>\n",
       "      <td id=\"T_5e260_row3_col4\" class=\"data row3 col4\" >-0.09%</td>\n",
       "      <td id=\"T_5e260_row3_col5\" class=\"data row3 col5\" >-2.62%</td>\n",
       "      <td id=\"T_5e260_row3_col6\" class=\"data row3 col6\" >-2.46%</td>\n",
       "      <td id=\"T_5e260_row3_col7\" class=\"data row3 col7\" >2.11%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row4\" class=\"row_heading level0 row4\" >5.380000</th>\n",
       "      <td id=\"T_5e260_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_5e260_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_5e260_row4_col2\" class=\"data row4 col2\" >-1.05%</td>\n",
       "      <td id=\"T_5e260_row4_col3\" class=\"data row4 col3\" >-0.99%</td>\n",
       "      <td id=\"T_5e260_row4_col4\" class=\"data row4 col4\" >-2.23%</td>\n",
       "      <td id=\"T_5e260_row4_col5\" class=\"data row4 col5\" >-1.19%</td>\n",
       "      <td id=\"T_5e260_row4_col6\" class=\"data row4 col6\" >-1.57%</td>\n",
       "      <td id=\"T_5e260_row4_col7\" class=\"data row4 col7\" >2.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row5\" class=\"row_heading level0 row5\" >7.530000</th>\n",
       "      <td id=\"T_5e260_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_5e260_row5_col1\" class=\"data row5 col1\" >-1.41%</td>\n",
       "      <td id=\"T_5e260_row5_col2\" class=\"data row5 col2\" >-1.49%</td>\n",
       "      <td id=\"T_5e260_row5_col3\" class=\"data row5 col3\" >0.03%</td>\n",
       "      <td id=\"T_5e260_row5_col4\" class=\"data row5 col4\" >-2.89%</td>\n",
       "      <td id=\"T_5e260_row5_col5\" class=\"data row5 col5\" >0.19%</td>\n",
       "      <td id=\"T_5e260_row5_col6\" class=\"data row5 col6\" >-2.15%</td>\n",
       "      <td id=\"T_5e260_row5_col7\" class=\"data row5 col7\" >3.56%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row6\" class=\"row_heading level0 row6\" >10.540000</th>\n",
       "      <td id=\"T_5e260_row6_col0\" class=\"data row6 col0\" ></td>\n",
       "      <td id=\"T_5e260_row6_col1\" class=\"data row6 col1\" >-1.49%</td>\n",
       "      <td id=\"T_5e260_row6_col2\" class=\"data row6 col2\" >-2.30%</td>\n",
       "      <td id=\"T_5e260_row6_col3\" class=\"data row6 col3\" >1.56%</td>\n",
       "      <td id=\"T_5e260_row6_col4\" class=\"data row6 col4\" >2.83%</td>\n",
       "      <td id=\"T_5e260_row6_col5\" class=\"data row6 col5\" >0.62%</td>\n",
       "      <td id=\"T_5e260_row6_col6\" class=\"data row6 col6\" >1.63%</td>\n",
       "      <td id=\"T_5e260_row6_col7\" class=\"data row6 col7\" >5.67%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row7\" class=\"row_heading level0 row7\" >14.760000</th>\n",
       "      <td id=\"T_5e260_row7_col0\" class=\"data row7 col0\" >-3.71%</td>\n",
       "      <td id=\"T_5e260_row7_col1\" class=\"data row7 col1\" >-1.90%</td>\n",
       "      <td id=\"T_5e260_row7_col2\" class=\"data row7 col2\" >-0.43%</td>\n",
       "      <td id=\"T_5e260_row7_col3\" class=\"data row7 col3\" >-0.11%</td>\n",
       "      <td id=\"T_5e260_row7_col4\" class=\"data row7 col4\" >1.43%</td>\n",
       "      <td id=\"T_5e260_row7_col5\" class=\"data row7 col5\" >0.25%</td>\n",
       "      <td id=\"T_5e260_row7_col6\" class=\"data row7 col6\" >1.46%</td>\n",
       "      <td id=\"T_5e260_row7_col7\" class=\"data row7 col7\" >9.94%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row8\" class=\"row_heading level0 row8\" >20.660000</th>\n",
       "      <td id=\"T_5e260_row8_col0\" class=\"data row8 col0\" ></td>\n",
       "      <td id=\"T_5e260_row8_col1\" class=\"data row8 col1\" >-2.59%</td>\n",
       "      <td id=\"T_5e260_row8_col2\" class=\"data row8 col2\" >-1.87%</td>\n",
       "      <td id=\"T_5e260_row8_col3\" class=\"data row8 col3\" >0.24%</td>\n",
       "      <td id=\"T_5e260_row8_col4\" class=\"data row8 col4\" >3.08%</td>\n",
       "      <td id=\"T_5e260_row8_col5\" class=\"data row8 col5\" >4.19%</td>\n",
       "      <td id=\"T_5e260_row8_col6\" class=\"data row8 col6\" >2.01%</td>\n",
       "      <td id=\"T_5e260_row8_col7\" class=\"data row8 col7\" >9.47%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row9\" class=\"row_heading level0 row9\" >28.930000</th>\n",
       "      <td id=\"T_5e260_row9_col0\" class=\"data row9 col0\" >-4.50%</td>\n",
       "      <td id=\"T_5e260_row9_col1\" class=\"data row9 col1\" >-2.06%</td>\n",
       "      <td id=\"T_5e260_row9_col2\" class=\"data row9 col2\" >0.30%</td>\n",
       "      <td id=\"T_5e260_row9_col3\" class=\"data row9 col3\" >0.44%</td>\n",
       "      <td id=\"T_5e260_row9_col4\" class=\"data row9 col4\" >1.61%</td>\n",
       "      <td id=\"T_5e260_row9_col5\" class=\"data row9 col5\" >1.73%</td>\n",
       "      <td id=\"T_5e260_row9_col6\" class=\"data row9 col6\" >1.88%</td>\n",
       "      <td id=\"T_5e260_row9_col7\" class=\"data row9 col7\" >5.97%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row10\" class=\"row_heading level0 row10\" >40.500000</th>\n",
       "      <td id=\"T_5e260_row10_col0\" class=\"data row10 col0\" ></td>\n",
       "      <td id=\"T_5e260_row10_col1\" class=\"data row10 col1\" >-2.98%</td>\n",
       "      <td id=\"T_5e260_row10_col2\" class=\"data row10 col2\" >0.07%</td>\n",
       "      <td id=\"T_5e260_row10_col3\" class=\"data row10 col3\" >-0.03%</td>\n",
       "      <td id=\"T_5e260_row10_col4\" class=\"data row10 col4\" >1.93%</td>\n",
       "      <td id=\"T_5e260_row10_col5\" class=\"data row10 col5\" >3.72%</td>\n",
       "      <td id=\"T_5e260_row10_col6\" class=\"data row10 col6\" >-1.17%</td>\n",
       "      <td id=\"T_5e260_row10_col7\" class=\"data row10 col7\" >9.14%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row11\" class=\"row_heading level0 row11\" >56.690000</th>\n",
       "      <td id=\"T_5e260_row11_col0\" class=\"data row11 col0\" ></td>\n",
       "      <td id=\"T_5e260_row11_col1\" class=\"data row11 col1\" >-1.61%</td>\n",
       "      <td id=\"T_5e260_row11_col2\" class=\"data row11 col2\" >-1.04%</td>\n",
       "      <td id=\"T_5e260_row11_col3\" class=\"data row11 col3\" >1.24%</td>\n",
       "      <td id=\"T_5e260_row11_col4\" class=\"data row11 col4\" >-0.28%</td>\n",
       "      <td id=\"T_5e260_row11_col5\" class=\"data row11 col5\" >4.48%</td>\n",
       "      <td id=\"T_5e260_row11_col6\" class=\"data row11 col6\" >-3.24%</td>\n",
       "      <td id=\"T_5e260_row11_col7\" class=\"data row11 col7\" >9.19%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row12\" class=\"row_heading level0 row12\" >79.370000</th>\n",
       "      <td id=\"T_5e260_row12_col0\" class=\"data row12 col0\" ></td>\n",
       "      <td id=\"T_5e260_row12_col1\" class=\"data row12 col1\" >-2.57%</td>\n",
       "      <td id=\"T_5e260_row12_col2\" class=\"data row12 col2\" >-4.13%</td>\n",
       "      <td id=\"T_5e260_row12_col3\" class=\"data row12 col3\" ></td>\n",
       "      <td id=\"T_5e260_row12_col4\" class=\"data row12 col4\" >-4.43%</td>\n",
       "      <td id=\"T_5e260_row12_col5\" class=\"data row12 col5\" >-2.41%</td>\n",
       "      <td id=\"T_5e260_row12_col6\" class=\"data row12 col6\" ></td>\n",
       "      <td id=\"T_5e260_row12_col7\" class=\"data row12 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row13\" class=\"row_heading level0 row13\" >111.120000</th>\n",
       "      <td id=\"T_5e260_row13_col0\" class=\"data row13 col0\" ></td>\n",
       "      <td id=\"T_5e260_row13_col1\" class=\"data row13 col1\" >-3.13%</td>\n",
       "      <td id=\"T_5e260_row13_col2\" class=\"data row13 col2\" >-4.80%</td>\n",
       "      <td id=\"T_5e260_row13_col3\" class=\"data row13 col3\" ></td>\n",
       "      <td id=\"T_5e260_row13_col4\" class=\"data row13 col4\" ></td>\n",
       "      <td id=\"T_5e260_row13_col5\" class=\"data row13 col5\" ></td>\n",
       "      <td id=\"T_5e260_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "      <td id=\"T_5e260_row13_col7\" class=\"data row13 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5e260_level0_row14\" class=\"row_heading level0 row14\" >155.570000</th>\n",
       "      <td id=\"T_5e260_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_5e260_row14_col1\" class=\"data row14 col1\" >-3.60%</td>\n",
       "      <td id=\"T_5e260_row14_col2\" class=\"data row14 col2\" >-5.79%</td>\n",
       "      <td id=\"T_5e260_row14_col3\" class=\"data row14 col3\" ></td>\n",
       "      <td id=\"T_5e260_row14_col4\" class=\"data row14 col4\" ></td>\n",
       "      <td id=\"T_5e260_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_5e260_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "      <td id=\"T_5e260_row14_col7\" class=\"data row14 col7\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x28b2303d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.03983113086290058\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0125\n",
      "Universal Metric of SM2: 0.0823\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
